# NOT RUN {
# use of strata and labels
ggplot(as.data.frame(Titanic),
aes(y = Freq,
axis1 = Class, axis2 = Sex, axis3 = Age)) +
geom_flow() +
scale_x_discrete(limits = c("Class", "Sex", "Age")) +
geom_stratum() + geom_text(stat = "stratum", infer.label = TRUE) +
ggtitle("Alluvial plot of Titanic passenger demographic data")
# use of facets
ggplot(as.data.frame(Titanic),
aes(y = Freq,
axis1 = Class, axis2 = Sex)) +
geom_flow(aes(fill = Age), width = .4) +
geom_stratum(width = .4) +
geom_text(stat = "stratum", infer.label = TRUE, size = 3) +
scale_x_discrete(limits = c("Class", "Sex")) +
facet_wrap(~ Survived, scales = "fixed")
# time series alluvia of WorldPhones data
wph <- as.data.frame(as.table(WorldPhones))
names(wph) <- c("Year", "Region", "Telephones")
ggplot(wph,
aes(x = Year, alluvium = Region, y = Telephones)) +
geom_flow(aes(fill = Region, colour = Region), width = 0)
# rightward flow aesthetics for vaccine survey data
data(vaccinations)
levels(vaccinations$response) <- rev(levels(vaccinations$response))
ggplot(vaccinations,
aes(x = survey, stratum = response, alluvium = subject,
y = freq, fill = response, label = round(a, 3))) +
geom_lode() + geom_flow() +
geom_stratum(alpha = 0) +
geom_text(stat = "stratum")
# }
Run the code above in your browser using DataLab